Triple

T15846924
Position Surface form Disambiguated ID Type / Status
Subject Mourão E384237 entity
Predicate locatedIn P40 FINISHED
Object Évora District NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Évora District | Statement: [Mourão, locatedIn, Évora District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Évora District
Context triple: [Mourão, locatedIn, Évora District]
  • A. Évora District chosen
    Évora District is an administrative region in southern Portugal known for its historic city of Évora, a UNESCO World Heritage site rich in Roman and medieval heritage.
  • B. Coimbra District
    Coimbra District is an administrative region in central Portugal that includes the historic university city of Coimbra and surrounding municipalities.
  • C. Setúbal District
    Setúbal District is an administrative region in southwestern Portugal known for its Atlantic coastline, industrial port city of Setúbal, and proximity to the Sado Estuary and Arrábida Natural Park.
  • D. Portalegre District
    Portalegre District is an administrative district in eastern Portugal, known for its historic towns and location along the Spanish border in the Alentejo region.
  • E. Covilhã District
    Covilhã District is a region in central Portugal known for its mountainous landscapes near Serra da Estrela and its historical textile industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14ca7c8f08190abe21cbb0c390f95 completed April 16, 2026, 8:55 p.m.
Created at: April 10, 2026, 4:50 a.m.